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Asked 3 months ago · Viewed 3,320 times
हिन्दी English

Who is the proponent of the Expectancy Theory?

Detailed Explanation

📌 Core Theoretical Concept:

The Expectancy Theory of learning, also known as Purposive Behaviorism or Sign-Gestalt Learning Theory, was propounded by the eminent American psychologist Edward C. Tolman. According to Tolman, learning is not merely a mechanical stimulus-response (S-R) connection, but rather a goal-directed and purposeful activity. He argued that organisms learn the meaning of environmental signs and form a 'Cognitive Map' in their minds to reach a specific goal. The expectancy component highlights that learners form an expectation that a particular behavior will lead to a specific reward or outcome.

📊 Key Exam Points:

  • Tolman's Contribution: Introduced foundational concepts like 'Latent Learning' and 'Cognitive Maps' bridging behaviorism and cognitive psychology.
  • Option 'a' (Alfred Binet): Known as the father of intelligence testing, he developed the first practical intelligence scale (Binet-Simon Scale).
  • Option 'c' (Jean Piaget): A Swiss psychologist renowned for his stage theory of Cognitive Development.
  • Option 'd' (Froebel): The pioneer of the Kindergarten educational system emphasizing play-way methods.

📖 Theoretical Reference: Tolman's Sign-Gestalt theory views behavior as holistic and goal-oriented. For comprehensive revision, explore topics related to Learning Theories and educational psychology frameworks.

🎯 Exam Perspective: Key Insights for Teacher Exams Detailed Solution ➔
Deep Pedagogical Analysis:

Questions concerning learning theorists and their core propositions frequently appear in teacher eligibility tests like CTET, DSSSB, KVS, and state TETs. Understanding Tolman's expectancy framework helps educators design classrooms that encourage cognitive mapping, where students understand the 'why' behind tasks rather than rote memorization. This purposeful approach enhances intrinsic motivation and helps students navigate complex problem-solving scenarios efficiently.

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